Leveraging Complexity Science to Promote Learning Analytics Adoption in Higher Education: An Embedded Case Study
dc.contributor.advisor | Ketelhut, Diane J | en_US |
dc.contributor.author | Moses, Phillip Scott | en_US |
dc.contributor.department | Education Policy, and Leadership | en_US |
dc.contributor.publisher | Digital Repository at the University of Maryland | en_US |
dc.contributor.publisher | University of Maryland (College Park, Md.) | en_US |
dc.date.accessioned | 2024-09-23T05:51:45Z | |
dc.date.available | 2024-09-23T05:51:45Z | |
dc.date.issued | 2024 | en_US |
dc.description.abstract | The Society for Learning Analytics Research (SoLAR) defines learning analytics as “the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs” (SoLAR, n.d.). To fully realize the potential of learning analytics, especially in its perceived ability to reveal previously hidden aspects of the learning process, researchers have called for more intentional approaches in order to harness resources and affect change. These researchers argue that without this coordinated effort to integrate learning analytics into the fabric of higher education institutions, the field will continue to languish, with learning analytics tools and approaches left forever incapable of affecting more systemic change. At the same time, other researchers focused on leadership and change management have recognized the difficulty, if not impossibility, of such top-down approaches. Instead, many researchers have pointed to the need to view higher education institutions through the lens of complexity science, and, in particular, to consider higher education institutions as complex adaptive systems (CAS) in which change tends to happen through the process of emergence. Within such a paradigm, change occurs from the ground up, as a result of countless interactions among many different agents (students, educators, and administrators, to name a few). Recognizing this conflict between the sort of top-down approaches suggested by many learning analytics researchers, and the ground-up reality recognized by many complexity science researchers, this dissertation project investigates how learning analytics usage is happening within a higher education institution. Using an embedded case study methodology to examine current learning analytics practices across multiple academic units and stakeholders within a single higher education institution, I apply a CAS framework to determine how this institution might expand and grow their approach to learning analytics across key areas. | en_US |
dc.identifier | https://doi.org/10.13016/8rxr-cjz7 | |
dc.identifier.uri | http://hdl.handle.net/1903/33334 | |
dc.language.iso | en | en_US |
dc.subject.pqcontrolled | Educational leadership | en_US |
dc.subject.pqcontrolled | Educational technology | en_US |
dc.subject.pquncontrolled | Complexity Science | en_US |
dc.subject.pquncontrolled | Higher Education | en_US |
dc.subject.pquncontrolled | Learning Analytics | en_US |
dc.subject.pquncontrolled | Learning Management Systems | en_US |
dc.title | Leveraging Complexity Science to Promote Learning Analytics Adoption in Higher Education: An Embedded Case Study | en_US |
dc.type | Dissertation | en_US |
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